About Gnani.ai:
Gnani.ai is a frontier Voice AI company, building best-in-class AI models and agentic AI platforms that solve problems at scale. Our proprietary stack — speech recognition, text-to-speech, small language models, and agentic voice platforms across 40+ languages — powers real-time conversations in production for some of the most demanding enterprises in the world.
We own our stack end to end. That is our moat — and product is how we turn that depth into experiences customers and developers love.
Location
Bengaluru | Individual Contributor | 7+ Years Experience
About the Role-
We are building a mission-critical, multi-tenant Voice AI platform that powers tens of millions of conversations every day with sub-second response times. The platform combines real-time audio streaming, large-scale distributed systems, AI model orchestration, analytics, billing, and observability into a single developer platform.
As a Sr. Staff Engineer, you will serve as one of the principal technical leaders for the organization. You will own architectural direction across multiple systems, drive engineering excellence, and make foundational decisions that influence the scalability, reliability, and evolution of the platform for years to come.
This is a hands-on leadership role. You will be expected to write production code, review critical designs, mentor senior engineers, author RFCs, and lead cross-functional initiatives while remaining deeply involved in technical execution.
Key Responsibilities-
- Own the end-to-end architecture of the Voice AI platform, defining how requests, audio streams, model interactions, and responses flow through the system.
- Design and scale highly available distributed systems capable of supporting tens of millions of daily interactions while maintaining stringent latency and reliability objectives.
- Lead the evolution of our real-time media infrastructure, including WebSockets, streaming pipelines, queueing systems, model orchestration, and event-driven architectures.
- Architect audio-processing systems encompassing TTS segmentation, audio transcoding, sample-rate conversion, VAD-based silence detection, and ASR workflows.
- Establish platform-wide engineering standards for performance, reliability, security, observability, testing, and operational excellence.
- Drive the design of platform services including metering, billing, rate limiting, tenant isolation, quota management, and usage analytics.
- Build scalable observability systems leveraging metrics, distributed tracing, logging, and alerting to accelerate incident response and troubleshooting.
- Partner closely with product, infrastructure, AI, and leadership teams to translate business goals into scalable technical strategies.
- Champion a documentation-first engineering culture through architecture reviews, design documents, RFCs, and technical roadmaps.
- Mentor senior engineers and act as a force multiplier across the engineering organization.
What We're Looking For-
- 7+ years of experience designing, building, and operating large-scale backend platforms in production environments.
- Demonstrated success leading the architecture of distributed systems with demanding requirements around scale, availability, and latency.
- Deep expertise in Go and strong Python proficiency, with extensive experience delivering production-grade services and APIs.
- Strong understanding of real-time communication systems, streaming architectures, back-pressure management, and long-lived connection handling.
- Expertise in data platforms including ClickHouse, MongoDB, PostgreSQL, and Redis, with a focus on performance optimization and scalability.
- Experience designing analytics and event-processing pipelines capable of handling high-volume workloads.
- Proven track record building and operating SaaS platforms, including multi-tenant architectures, customer-facing APIs, and operational governance.
- Strong Kubernetes experience, including production operations, StatefulSets, networking, service discovery, and large-scale deployments.
- Exceptional engineering judgment with the ability to balance short-term delivery needs against long-term platform investments.
- Strong written and verbal communication skills, with the ability to influence technical direction across teams.
Preferred Qualifications-
- Experience deploying or operating LLM, ASR, TTS, or other AI inference systems at scale.
- Experience building low-latency infrastructure where milliseconds directly impact customer experience.
- Background in platform engineering, developer tooling, or infrastructure products.
- Experience working in high-growth startups or fast-scaling technology organizations.
- Contributions to open-source projects, technical communities, or engineering thought leadership.
Technology Stack
Go · Python · FastAPI · gRPC · NATS JetStream · RabbitMQ · WebSockets · ClickHouse · MongoDB · PostgreSQL · Redis · Kubernetes (Azure AKS) · Prometheus · OpenTelemetry
Why Join Us-
- Build foundational technology powering millions of AI-driven conversations.
- Work on technically challenging problems across distributed systems, real-time media, AI infrastructure, and large-scale data platforms.
- Operate with significant ownership, autonomy, and influence over technical strategy.
- Collaborate with a highly capable team solving complex engineering challenges at scale.
